Danny--
The answer is no, you cannot "trust this result" from a command that
does not allow cluster-robust estimation when you must use clustered
standard errors in the IV (ivreg2) estimation. If clustering is
important, and you have said that it is, and you have a weak
instruments problem, you must either improve the quality of your
instruments by adding/finding more excluded instruments, in which case
you probably want the LIML/CUE options on -ivreg2- (and overID tests),
or you can use a method of inference robust to the presence of weak
instruments that allows clustering, namely Anderson-Rubin tests/conf
regions. I discussed this in some detail at NASUG5, and some of the
material appears in the slides athttp://www.stata.com/meeting/5nasug/wiv.pdf and some in Stata Journal
7(4). On Anderson-Rubin tests/conf regions, see the Dufour and
Taamouti ref linked from http://www.stata.com/meeting/5nasug/wiv.pdf
(though I prefer constructing the confidence region rather than the
projection onto individual axes that they advocate--the latter can be
deceptive if, say, there are two variables measuring a similar
quantity and you can reject that both coefs are simultaneously zero
because the conf ellipse does not include the origin, but the
projections might both overlap zero). Tests are easier than
confidence regions for this approach, obviously.